Show simple item record

dc.contributor.authorAlfonso, J C L
dc.contributor.authorSchaadt, N S
dc.contributor.authorSchönmeyer, R
dc.contributor.authorBrieu, N
dc.contributor.authorForestier, G
dc.contributor.authorWemmert, C
dc.contributor.authorFeuerhake, F
dc.contributor.authorHatzikirou, H
dc.date.accessioned2016-10-12T07:54:50Z
dc.date.available2016-10-12T07:54:50Z
dc.date.issued2016-10-12
dc.identifier.citationIn-silico insights on the prognostic potential of immune cell infiltration patterns in the breast lobular epithelium., 6:33322 Sci Repen
dc.identifier.issn2045-2322
dc.identifier.pmid27659691
dc.identifier.doi10.1038/srep33322
dc.identifier.urihttp://hdl.handle.net/10033/620546
dc.description.abstractScattered inflammatory cells are commonly observed in mammary gland tissue, most likely in response to normal cell turnover by proliferation and apoptosis, or as part of immunosurveillance. In contrast, lymphocytic lobulitis (LLO) is a recurrent inflammation pattern, characterized by lymphoid cells infiltrating lobular structures, that has been associated with increased familial breast cancer risk and immune responses to clinically manifest cancer. The mechanisms and pathogenic implications related to the inflammatory microenvironment in breast tissue are still poorly understood. Currently, the definition of inflammation is mainly descriptive, not allowing a clear distinction of LLO from physiological immunological responses and its role in oncogenesis remains unclear. To gain insights into the prognostic potential of inflammation, we developed an agent-based model of immune and epithelial cell interactions in breast lobular epithelium. Physiological parameters were calibrated from breast tissue samples of women who underwent reduction mammoplasty due to orthopedic or cosmetic reasons. The model allowed to investigate the impact of menstrual cycle length and hormone status on inflammatory responses to cell turnover in the breast tissue. Our findings suggested that the immunological context, defined by the immune cell density, functional orientation and spatial distribution, contains prognostic information previously not captured by conventional diagnostic approaches.
dc.languageENG
dc.language.isoen_USen
dc.rights.urihttp://creativecommons.org/licenses/by-nc-sa/4.0/*
dc.titleIn-silico insights on the prognostic potential of immune cell infiltration patterns in the breast lobular epithelium.en_US
dc.typeArticleen
dc.contributor.departmentBRICS, Braunschweiger Zentrum für Systembiologie, Rebenring 56, 38106 Braunschweig, Germany.en
dc.identifier.journalScientific reportsen
refterms.dateFOA2018-06-13T16:03:28Z
html.description.abstractScattered inflammatory cells are commonly observed in mammary gland tissue, most likely in response to normal cell turnover by proliferation and apoptosis, or as part of immunosurveillance. In contrast, lymphocytic lobulitis (LLO) is a recurrent inflammation pattern, characterized by lymphoid cells infiltrating lobular structures, that has been associated with increased familial breast cancer risk and immune responses to clinically manifest cancer. The mechanisms and pathogenic implications related to the inflammatory microenvironment in breast tissue are still poorly understood. Currently, the definition of inflammation is mainly descriptive, not allowing a clear distinction of LLO from physiological immunological responses and its role in oncogenesis remains unclear. To gain insights into the prognostic potential of inflammation, we developed an agent-based model of immune and epithelial cell interactions in breast lobular epithelium. Physiological parameters were calibrated from breast tissue samples of women who underwent reduction mammoplasty due to orthopedic or cosmetic reasons. The model allowed to investigate the impact of menstrual cycle length and hormone status on inflammatory responses to cell turnover in the breast tissue. Our findings suggested that the immunological context, defined by the immune cell density, functional orientation and spatial distribution, contains prognostic information previously not captured by conventional diagnostic approaches.


Files in this item

Thumbnail
Name:
Alfonso et al.pdf
Size:
4.449Mb
Format:
PDF
Description:
Open Access publication

This item appears in the following Collection(s)

Show simple item record

http://creativecommons.org/licenses/by-nc-sa/4.0/
Except where otherwise noted, this item's license is described as http://creativecommons.org/licenses/by-nc-sa/4.0/